Qlik Answers vs. Copilot

While we don't know much about it, Qlik on QlikConnect global event just announced Qlik Answers - RAG based, GenAI tool for analytics. I decided to gather what I know and compare it with its nemezis - Copilot. So, what do we know?

Copilot for Power BI

Pros:

• Integrated Ecosystem: Seamlessly integrates with Power BI and whole Microsoft suite, leveraging existing data models and report structures, which allows users to build on their current BI infrastructure.
• Natural Language Querying: Enables users to ask questions in natural language, simplifying data exploration for non-technical users.
• Automated Report Generation: Automatically generates report pages based on high-level prompts, saving significant time and effort in report creation.
• Data Summarization: Provides narrative summaries of reports, specific pages, or individual visuals, aiding in quickly understanding key insights.

Cons:

• Workspace Requirements: Requires access to Premium or Fabric capacity workspaces, which can be a limitation for some users, both cost and architecture wide.
• Complex Prompts: May struggle with complex prompts, potentially generating irrelevant visuals.
• Limited Visual Customization: Does not support post-generation visual modifications or layout changes.
• Learning Curve: Users need to understand how to optimize their data models for the best results.

RAG Architecture: Copilot for Power BI utilizes Retrieval-Augmented Generation (RAG) to enhance its capabilities, providing more accurate and contextually relevant responses by retrieving and incorporating the most recent and relevant data into the AI's responses. This architecture is beneficial for maintaining up-to-date and precise insights in dynamic data environments.

Qlik Answers

Pros:

• Conversational Analytics: Allows users to interact with data using natural language, making it accessible for non-technical users and enhancing user engagement.
• Real-Time Insights: Provides real-time insights and supports real-time analytics integration, allowing users to ask questions and get immediate answers based on current data.
• AI-Driven Features: Supports various AI-driven features such as automated insights, natural language generation, and data augmentation using OpenAI connectors.

Cons:

• Limited Dashboard Creation: Unlike Copilot for Power BI, Qlik Answers does not generate entire dashboards but focuses on providing insights and answering queries using generative AI.
• Dependency on Qlik Ecosystem: Users must be within the Qlik Sense environment to utilize Qlik Answers, which might not be ideal for those using other BI tools.
• Complex Query Handling: May require specific phrasing for complex queries to ensure accurate responses, which can be a learning curve for users.

RAG Architecture: Qlik Answers employs RAG to provide accurate and contextually relevant responses by retrieving and incorporating the most up-to-date data. This architecture allows the system to offer grounded and relevant insights based on the latest available information.

Summary

Copilot for Power BI is ideal for users who need automated report generation and in-depth data summarization within the Microsoft ecosystem. Its RAG-based architecture enhances its ability to provide accurate, up-to-date insights.

Qlik Answers excels in providing real-time, conversational analytics within the Qlik ecosystem. It leverages RAG to offer immediate and contextually relevant insights, although it does not create entire dashboards.

What do you think about using GenAI in your data tool?

Are you excited about it? Or you don't think it'll revolutionize the way we interact with the data? Share your ideas in the comment.

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